The prediction of traffic accident duration is the basis of highway emergency management. Timely and accurate prediction of traffic accident duration can provide a reliable basis for road guidance and rescue organization. This paper discusses the traffic accident duration prediction method of N-BEATS model in detail. Through the change of sliding window size and the continuous adjustment of the number of iterations, the appropriate parameters are found to produce a good prediction effect. The dataset used in this paper is US Accidents, a nation-wide dataset of traffic accidents covering 49 states in the US. The experimental results show that compared with the classical time series prediction models such as Bi-LSTM, SVM, RNN-GRU and AttnAR, prediction of traffic accident duration model based on N-BEATS proposed in this paper is optimal in the three evaluation indicators of RMSE, MAE and SD, which shows that the model has the highest prediction accuracy and good performance.
Prediction of traffic accident duration based on N-BEATS
Second International Conference on Algorithms, Microchips, and Network Applications (AMNA 2023) ; 2023 ; Zhengzhou, China
Proc. SPIE ; 12635
2023-05-08
Conference paper
Electronic Resource
English
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